Analysis of central transfer funds and the probability of corruption at the local government level using the Zero-Inflated Poisson method

Article Sidebar

Fulltext PDF Fulltext PDF (Bahasa Indonesia)
Published: Jun 25, 2022
DOI: https://doi.org/10.32697/integritas.v8i1.862
Keywords:
Corruption General Transfer Fund Special Transfer Fund Zero-Inflated Poisson

Main Article Content

Aan Dwi Nurcahyo
Komisi Pemberantasan Korupsi (KPK)
Benedictus Raksaka Mahi
Universitas Indonesia

Abstract

The majority of corruption in the regions in Indonesia is carried out on Regional Budget funds, which the main source of Regional Budget revenue comes from Central Government transfers. Based on the characteristics of their use, transfer funds can be classified into General Purpose Transfers (DTU) and Specific Purpose Transfers (DTK). This study was conducted to see the influence of DTU and DTK on the probability of corruption in the regions. The method used is Zero-Inflated Poisson (ZIP) regression because there is an overdispersion problem and excess zero in the dependent variable. With a sample of 519 Regency and City Governments in Indonesia in the 2010-2019 period, DTU was found to have a positive relationship to the level of corruption. The flexibility in managing the DTU budget is the cause that triggers an increase in corruption in the regions. Meanwhile, DTK shows a negative relationship with the level of corruption. The local government does not have the flexibility to use the DTK budget for other programs, and the supervision in the realization of the DTK program is also tighter.

Article Details

How to Cite
Nurcahyo, A. D., & Mahi, B. R. (2022). Analysis of central transfer funds and the probability of corruption at the local government level using the Zero-Inflated Poisson method. Integritas : Jurnal Antikorupsi, 8(1), 95–102. https://doi.org/10.32697/integritas.v8i1.862
Issue
Vol. 8 No. 1 (2022): INTEGRITAS: Jurnal Antikorupsi
Section
Articles
Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

References

Astuti, Y. D., & Adrison, V. (2019). The audit board of Republic of Indonesia opinion and bribery in local governments in Indonesia. Jurnal Tata Kelola Dan Akuntabilitas Keuangan Negara, 5(2), 125–138. https://doi.org/10.28986/jtaken.v5i2.379

Baskaran, T. (2011). Fiscal decentralization, ideology, and the size of the public sector. European Journal of Political Economy, 27(3), 485–506. https://doi.org/10.1016/j.ejpoleco.2011.03.003

Fatkuroji, I., & Meilinda, S. D. (2022). Pilihan publik dalam serial kasus korupsi kepala daerah. Integritas : Jurnal Antikorupsi, 7(2), 345–358. https://doi.org/10.32697/integritas.v7i2.799

Fittriyah, N., Hadi, A. F., & Dewi, Y. S. (2014). Pemodelan jumlah kematian akibat difteri di Provinsi Jawa Timur dengan Regresi Binomial Negatif dan Zero-Inflated Poisson. Prosiding Seminar Nasional Matematika, November, 201–214. https://jurnal.unej.ac.id/index.php/psmp/article/view/951

Goel, R. K., & Nelson, M. A. (2011). Towards an idea-centered, principle-base design to as creation approach support learning knowledge. Public Choice, 148(3), 471–490.

Hubbard, P. (2008). Putting the power of transparency in context: information’s role in reducing corruption in Uganda’s Education Sector. SSRN Electronic Journal, 136. https://doi.org/10.2139/ssrn.1100131

Kotera, G., Okada, K., & Samreth, S. (2012). Government size, democracy, and corruption: An empirical investigation. Economic Modelling, 29(6), 2340–2348. https://doi.org/10.1016/j.econmod.2012.06.022

Kusuma, W., Komalasari, D., & Hadijati, M. (2013). Model regresi Zero Inflated Poisson pada data overdispersion. Jurnal Matematika, 3(2), 71–85. https://doi.org/10.24843/JMAT.2013.v03.i02.p37

Lessmann, C., & Markwardt, G. (2010). One size fits all? Decentralization, corruption, and the monitoring of bureaucrats. World Development, 38(4), 631–646. https://doi.org/10.1016/j.worlddev.2009.11.003

Lou, Y.-I., & Wang, M.-L. (2011). Fraud risk factor of the fraud triangle assessing the likelihood of fraudulent financial reporting. Journal of Business & Economics Research (JBER), 7(2), 61–78. https://doi.org/10.19030/jber.v7i2.2262

Maria, E., Halim, A., & Suwardi, E. (2018). Eksplorasi faktor tekanan untuk melakukan fraud di pemerintah daerah Indonesia. Jurnal Akuntansi Publik, 1(1), 111–126. https://doi.org/10.32554/jap.v1.i1.p111-126

Saputra, B. (1969). Dampak desentralisasi fiskal terhadap korupsi di Indonesia. Jurnal Borneo Administrator, 8(3), 251–260. https://doi.org/10.24258/jba.v8i3.92

Sjahrir, B. S., Kis-Katos, K., & Schulze, G. G. (2013). Political budget cycles in Indonesia at the district level. Economics Letters, 120(2), 342–345. https://doi.org/10.1016/j.econlet.2013.05.007

Syurmita, S. (2014). Pengaruh karakteristik pemerintah daerah terhadap prediksi financial distress. Konferensi Regional Akuntansi (KRA) Dan Doktoral Kolokium 2014.